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<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li><li class="navelem"><a class="el" href="dir_49d1182a3b8dfb62757c53ae905481ad.html">impl</a></li>  </ul>
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<div class="title">IVFFlatScan.cu</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/**</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * This source code is licensed under the BSD+Patents license found in the</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &quot;IVFFlatScan.cuh&quot;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &quot;../GpuResources.h&quot;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &quot;IVFUtils.cuh&quot;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &quot;../utils/ConversionOperators.cuh&quot;</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceDefs.cuh&quot;</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceUtils.h&quot;</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceTensor.cuh&quot;</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#include &quot;../utils/Float16.cuh&quot;</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="preprocessor">#include &quot;../utils/MathOperators.cuh&quot;</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#include &quot;../utils/LoadStoreOperators.cuh&quot;</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="preprocessor">#include &quot;../utils/PtxUtils.cuh&quot;</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="preprocessor">#include &quot;../utils/Reductions.cuh&quot;</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#include &quot;../utils/StaticUtils.h&quot;</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#include &lt;thrust/host_vector.h&gt;</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="keyword">inline</span> __device__ <span class="keyword">typename</span> Math&lt;T&gt;::ScalarType l2Distance(T a, T b) {</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;  a = Math&lt;T&gt;::sub(a, b);</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;  a = Math&lt;T&gt;::mul(a, a);</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="structfaiss_1_1gpu_1_1Math.html#a4b17f0b5d014f300e76dde5b24af8014">Math&lt;T&gt;::reduceAdd</a>(a);</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;}</div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">inline</span> __device__ <span class="keyword">typename</span> Math&lt;T&gt;::ScalarType ipDistance(T a, T b) {</div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;  <span class="keywordflow">return</span> <a class="code" href="structfaiss_1_1gpu_1_1Math.html#a4b17f0b5d014f300e76dde5b24af8014">Math&lt;T&gt;::reduceAdd</a>(Math&lt;T&gt;::mul(a, b));</div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;}</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="comment">// For list scanning, even if the input data is `half`, we perform all</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="comment">// math in float32, because the code is memory b/w bound, and the</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="comment">// added precision for accumulation is useful</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="comment"></span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="comment">/// The class that we use to provide scan specializations</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="comment"></span><span class="keyword">template</span> &lt;<span class="keywordtype">int</span> Dims, <span class="keywordtype">bool</span> L2, <span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">   46</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a> {</div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;};</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="comment">// Fallback implementation: works for any dimension size</span></div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2, <span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan_3-1_00_01L2_00_01T_01_4.html">   51</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;-1, L2, T&gt; {</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="keyword">extern</span> __shared__ <span class="keywordtype">float</span> smem[];</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    T* vecs = (T*) vecData;</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> vec = 0; vec &lt; numVecs; ++vec) {</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;      <span class="comment">// Reduce in dist</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;      <span class="keywordtype">float</span> dist = 0.0f;</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> d = threadIdx.x; d &lt; dim; d += blockDim.x) {</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        <span class="keywordtype">float</span> vecVal = <a class="code" href="structfaiss_1_1gpu_1_1ConvertTo.html">ConvertTo&lt;float&gt;::to</a>(vecs[vec * dim + d]);</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        <span class="keywordtype">float</span> queryVal = query[d];</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <span class="keywordtype">float</span> curDist;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;          curDist = l2Distance(queryVal, vecVal);</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;          curDist = ipDistance(queryVal, vecVal);</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        }</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        dist += curDist;</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;      }</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;      <span class="comment">// Reduce distance within block</span></div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;      dist = blockReduceAllSum&lt;float, false, true&gt;(dist, smem);</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;      <span class="keywordflow">if</span> (threadIdx.x == 0) {</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        distanceOut[vec] = dist;</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;      }</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    }</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  }</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;};</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;<span class="comment">// implementation: works for # dims == blockDim.x</span></div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2, <span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00090"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan_3_010_00_01L2_00_01T_01_4.html">   90</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;0, L2, T&gt; {</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keyword">extern</span> __shared__ <span class="keywordtype">float</span> smem[];</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    T* vecs = (T*) vecData;</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    <span class="keywordtype">float</span> queryVal = query[threadIdx.x];</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll);</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; limit; i += kUnroll) {</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      <span class="keywordtype">float</span> vecVal[kUnroll];</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;        vecVal[j] = <a class="code" href="structfaiss_1_1gpu_1_1ConvertTo.html">ConvertTo&lt;float&gt;::to</a>(vecs[(i + j) * dim + threadIdx.x]);</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;      }</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;          vecVal[j] = l2Distance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;          vecVal[j] = ipDistance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;        }</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;      }</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      blockReduceAllSum&lt;kUnroll, float, false, true&gt;(vecVal, smem);</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;      <span class="keywordflow">if</span> (threadIdx.x == 0) {</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;          distanceOut[i + j] = vecVal[j];</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        }</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;      }</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    }</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit; i &lt; numVecs; ++i) {</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;      <span class="keywordtype">float</span> vecVal = <a class="code" href="structfaiss_1_1gpu_1_1ConvertTo.html">ConvertTo&lt;float&gt;::to</a>(vecs[i * dim + threadIdx.x]);</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        vecVal = l2Distance(queryVal, vecVal);</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        vecVal = ipDistance(queryVal, vecVal);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;      }</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;      vecVal = blockReduceAllSum&lt;float, false, true&gt;(vecVal, smem);</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;      <span class="keywordflow">if</span> (threadIdx.x == 0) {</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;        distanceOut[i] = vecVal;</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;      }</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    }</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  }</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;};</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;<span class="comment">// 64-d float32 implementation</span></div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00152"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan_3_0164_00_01L2_00_01float_01_4.html">  152</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;64, L2, float&gt; {</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 64;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;    <span class="comment">// Each warp reduces a single 64-d vector; each lane loads a float2</span></div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    <span class="keywordtype">float</span>* vecs = (<span class="keywordtype">float</span>*) vecData;</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="keywordtype">int</span> laneId = getLaneId();</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    <span class="keywordtype">int</span> numWarps = blockDim.x / kWarpSize;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    float2 queryVal = *(float2*) &amp;query[laneId * 2];</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    float2 vecVal[kUnroll];</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll * numWarps);</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = warpId; i &lt; limit; i += kUnroll * numWarps) {</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        <span class="comment">// Vector we are loading from is i</span></div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        <span class="comment">// Dim we are loading from is laneId * 2</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        vecVal[j] = *(float2*) &amp;vecs[(i + j * numWarps) * kDims + laneId * 2];</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;      }</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;      <span class="keywordtype">float</span> dist[kUnroll];</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;          dist[j] = l2Distance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;          dist[j] = ipDistance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;        }</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;      }</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      <span class="comment">// Reduce within the warp</span></div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;        dist[j] = warpReduceAllSum(dist[j]);</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      }</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;          distanceOut[i + j * numWarps] = dist[j];</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;        }</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;      }</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    }</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit + warpId; i &lt; numVecs; i += numWarps) {</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      vecVal[0] = *(float2*) &amp;vecs[i * kDims + laneId * 2];</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;      <span class="keywordtype">float</span> dist;</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        dist = l2Distance(queryVal, vecVal[0]);</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;        dist = ipDistance(queryVal, vecVal[0]);</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;      }</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;      dist = warpReduceAllSum(dist);</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        distanceOut[i] = dist;</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;      }</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    }</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  }</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;};</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;<span class="comment">// float16 implementation</span></div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;64, L2, half&gt; {</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 64;</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    <span class="comment">// Each warp reduces a single 64-d vector; each lane loads a half2</span></div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    half* vecs = (half*) vecData;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keywordtype">int</span> laneId = getLaneId();</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    <span class="keywordtype">int</span> numWarps = blockDim.x / kWarpSize;</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    float2 queryVal = *(float2*) &amp;query[laneId * 2];</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    half2 vecVal[kUnroll];</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll * numWarps);</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = warpId; i &lt; limit; i += kUnroll * numWarps) {</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        <span class="comment">// Vector we are loading from is i</span></div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;        <span class="comment">// Dim we are loading from is laneId * 2</span></div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        vecVal[j] = *(half2*) &amp;vecs[(i + j * numWarps) * kDims + laneId * 2];</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      }</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;      <span class="keywordtype">float</span> dist[kUnroll];</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;          dist[j] = l2Distance(queryVal, __half22float2(vecVal[j]));</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;          dist[j] = ipDistance(queryVal, __half22float2(vecVal[j]));</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;        }</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;      }</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;      <span class="comment">// Reduce within the warp</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        dist[j] = warpReduceAllSum(dist[j]);</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;      }</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;          distanceOut[i + j * numWarps] = dist[j];</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;        }</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;      }</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;    }</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit + warpId; i &lt; numVecs; i += numWarps) {</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;      vecVal[0] = *(half2*) &amp;vecs[i * kDims + laneId * 2];</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;      <span class="keywordtype">float</span> dist;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        dist = l2Distance(queryVal, __half22float2(vecVal[0]));</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        dist = ipDistance(queryVal, __half22float2(vecVal[0]));</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;      }</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;      dist = warpReduceAllSum(dist);</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        distanceOut[i] = dist;</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;      }</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    }</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;  }</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;};</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;<span class="comment">// 128-d float32 implementation</span></div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00310"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan_3_01128_00_01L2_00_01float_01_4.html">  310</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;128, L2, float&gt; {</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 128;</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;    <span class="comment">// Each warp reduces a single 128-d vector; each lane loads a float4</span></div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    <span class="keywordtype">float</span>* vecs = (<span class="keywordtype">float</span>*) vecData;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    <span class="keywordtype">int</span> laneId = getLaneId();</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;    <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <span class="keywordtype">int</span> numWarps = blockDim.x / kWarpSize;</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    float4 queryVal = *(float4*) &amp;query[laneId * 4];</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    float4 vecVal[kUnroll];</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll * numWarps);</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = warpId; i &lt; limit; i += kUnroll * numWarps) {</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;        <span class="comment">// Vector we are loading from is i</span></div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;        <span class="comment">// Dim we are loading from is laneId * 4</span></div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;        vecVal[j] = *(float4*) &amp;vecs[(i + j * numWarps) * kDims + laneId * 4];</div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;      }</div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;      <span class="keywordtype">float</span> dist[kUnroll];</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;          dist[j] = l2Distance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;          dist[j] = ipDistance(queryVal, vecVal[j]);</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;        }</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;      }</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;</div>
<div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;      <span class="comment">// Reduce within the warp</span></div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;        dist[j] = warpReduceAllSum(dist[j]);</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;      }</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;          distanceOut[i + j * numWarps] = dist[j];</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;        }</div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;      }</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;    }</div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit + warpId; i &lt; numVecs; i += numWarps) {</div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;      vecVal[0] = *(float4*) &amp;vecs[i * kDims + laneId * 4];</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;      <span class="keywordtype">float</span> dist;</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;        dist = l2Distance(queryVal, vecVal[0]);</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;        dist = ipDistance(queryVal, vecVal[0]);</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;      }</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;      dist = warpReduceAllSum(dist);</div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;        distanceOut[i] = dist;</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;      }</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;    }</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;  }</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;};</div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;<span class="comment">// float16 implementation</span></div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;128, L2, half&gt; {</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 128;</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;</div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;    <span class="comment">// Each warp reduces a single 128-d vector; each lane loads a Half4</span></div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;    half* vecs = (half*) vecData;</div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;    <span class="keywordtype">int</span> laneId = getLaneId();</div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;    <span class="keywordtype">int</span> numWarps = blockDim.x / kWarpSize;</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;    float4 queryVal = *(float4*) &amp;query[laneId * 4];</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;</div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    Half4 vecVal[kUnroll];</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll * numWarps);</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;</div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = warpId; i &lt; limit; i += kUnroll * numWarps) {</div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;        <span class="comment">// Vector we are loading from is i</span></div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;        <span class="comment">// Dim we are loading from is laneId * 4</span></div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;        vecVal[j] =</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;          <a class="code" href="structfaiss_1_1gpu_1_1LoadStore.html">LoadStore&lt;Half4&gt;::load</a>(</div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;            &amp;vecs[(i + j * numWarps) * kDims + laneId * 4]);</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;      }</div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;      <span class="keywordtype">float</span> dist[kUnroll];</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;</div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;          dist[j] = l2Distance(queryVal, half4ToFloat4(vecVal[j]));</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;          dist[j] = ipDistance(queryVal, half4ToFloat4(vecVal[j]));</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;        }</div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;      }</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;</div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;      <span class="comment">// Reduce within the warp</span></div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;        dist[j] = warpReduceAllSum(dist[j]);</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;      }</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;</div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;          distanceOut[i + j * numWarps] = dist[j];</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;        }</div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;      }</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;    }</div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit + warpId; i &lt; numVecs; i += numWarps) {</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;      vecVal[0] = LoadStore&lt;Half4&gt;::load(&amp;vecs[i * kDims + laneId * 4]);</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;      <span class="keywordtype">float</span> dist;</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;        dist = l2Distance(queryVal, half4ToFloat4(vecVal[0]));</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;        dist = ipDistance(queryVal, half4ToFloat4(vecVal[0]));</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;      }</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;      dist = warpReduceAllSum(dist);</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;</div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;        distanceOut[i] = dist;</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;      }</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;    }</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;  }</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;};</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;<span class="comment">// 256-d float32 implementation</span></div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00470"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IVFFlatScan_3_01256_00_01L2_00_01float_01_4.html">  470</a></span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;256, L2, float&gt; {</div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 256;</div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;    <span class="comment">// A specialization here to load per-warp seems to be worse, since</span></div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;    <span class="comment">// we&#39;re already running at near memory b/w peak</span></div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;    <a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan&lt;0, L2, float&gt;::scan</a>(query,</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;                                    vecData,</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;                                    numVecs,</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;                                    dim,</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;                                    distanceOut);</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;  }</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;};</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;</div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;<span class="comment">// float16 implementation</span></div>
<div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">bool</span> L2&gt;</div>
<div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;<span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IVFFlatScan.html">IVFFlatScan</a>&lt;256, L2, half&gt; {</div>
<div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;  <span class="keyword">static</span> constexpr <span class="keywordtype">int</span> kDims = 256;</div>
<div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;</div>
<div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;  <span class="keyword">static</span> __device__ <span class="keywordtype">void</span> scan(<span class="keywordtype">float</span>* query,</div>
<div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160;                              <span class="keywordtype">void</span>* vecData,</div>
<div class="line"><a name="l00497"></a><span class="lineno">  497</span>&#160;                              <span class="keywordtype">int</span> numVecs,</div>
<div class="line"><a name="l00498"></a><span class="lineno">  498</span>&#160;                              <span class="keywordtype">int</span> dim,</div>
<div class="line"><a name="l00499"></a><span class="lineno">  499</span>&#160;                              <span class="keywordtype">float</span>* distanceOut) {</div>
<div class="line"><a name="l00500"></a><span class="lineno">  500</span>&#160;    <span class="comment">// Each warp reduces a single 256-d vector; each lane loads a Half8</span></div>
<div class="line"><a name="l00501"></a><span class="lineno">  501</span>&#160;    half* vecs = (half*) vecData;</div>
<div class="line"><a name="l00502"></a><span class="lineno">  502</span>&#160;</div>
<div class="line"><a name="l00503"></a><span class="lineno">  503</span>&#160;    <span class="keywordtype">int</span> laneId = getLaneId();</div>
<div class="line"><a name="l00504"></a><span class="lineno">  504</span>&#160;    <span class="keywordtype">int</span> warpId = threadIdx.x / kWarpSize;</div>
<div class="line"><a name="l00505"></a><span class="lineno">  505</span>&#160;    <span class="keywordtype">int</span> numWarps = blockDim.x / kWarpSize;</div>
<div class="line"><a name="l00506"></a><span class="lineno">  506</span>&#160;</div>
<div class="line"><a name="l00507"></a><span class="lineno">  507</span>&#160;    <span class="comment">// This is not a contiguous load, but we only have to load these two</span></div>
<div class="line"><a name="l00508"></a><span class="lineno">  508</span>&#160;    <span class="comment">// values, so that we can load by Half8 below</span></div>
<div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;    float4 queryValA = *(float4*) &amp;query[laneId * 8];</div>
<div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;    float4 queryValB = *(float4*) &amp;query[laneId * 8 + 4];</div>
<div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;</div>
<div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    constexpr <span class="keywordtype">int</span> kUnroll = 4;</div>
<div class="line"><a name="l00513"></a><span class="lineno">  513</span>&#160;</div>
<div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;    Half8 vecVal[kUnroll];</div>
<div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;</div>
<div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;    <span class="keywordtype">int</span> limit = utils::roundDown(numVecs, kUnroll * numWarps);</div>
<div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160;</div>
<div class="line"><a name="l00518"></a><span class="lineno">  518</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = warpId; i &lt; limit; i += kUnroll * numWarps) {</div>
<div class="line"><a name="l00519"></a><span class="lineno">  519</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00520"></a><span class="lineno">  520</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00521"></a><span class="lineno">  521</span>&#160;        <span class="comment">// Vector we are loading from is i</span></div>
<div class="line"><a name="l00522"></a><span class="lineno">  522</span>&#160;        <span class="comment">// Dim we are loading from is laneId * 8</span></div>
<div class="line"><a name="l00523"></a><span class="lineno">  523</span>&#160;        vecVal[j] =</div>
<div class="line"><a name="l00524"></a><span class="lineno">  524</span>&#160;          <a class="code" href="structfaiss_1_1gpu_1_1LoadStore.html">LoadStore&lt;Half8&gt;::load</a>(</div>
<div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;          &amp;vecs[(i + j * numWarps) * kDims + laneId * 8]);</div>
<div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;      }</div>
<div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;</div>
<div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;      <span class="keywordtype">float</span> dist[kUnroll];</div>
<div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;</div>
<div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;        <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;          dist[j] = l2Distance(queryValA, half4ToFloat4(vecVal[j].a));</div>
<div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;          dist[j] += l2Distance(queryValB, half4ToFloat4(vecVal[j].b));</div>
<div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;        } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;          dist[j] = ipDistance(queryValA, half4ToFloat4(vecVal[j].a));</div>
<div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;          dist[j] += ipDistance(queryValB, half4ToFloat4(vecVal[j].b));</div>
<div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;        }</div>
<div class="line"><a name="l00539"></a><span class="lineno">  539</span>&#160;      }</div>
<div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;</div>
<div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;      <span class="comment">// Reduce within the warp</span></div>
<div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;        dist[j] = warpReduceAllSum(dist[j]);</div>
<div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160;      }</div>
<div class="line"><a name="l00546"></a><span class="lineno">  546</span>&#160;</div>
<div class="line"><a name="l00547"></a><span class="lineno">  547</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00548"></a><span class="lineno">  548</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00549"></a><span class="lineno">  549</span>&#160;<span class="preprocessor"></span>        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; kUnroll; ++j) {</div>
<div class="line"><a name="l00550"></a><span class="lineno">  550</span>&#160;          distanceOut[i + j * numWarps] = dist[j];</div>
<div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;        }</div>
<div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;      }</div>
<div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    }</div>
<div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;</div>
<div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;    <span class="comment">// Handle remainder</span></div>
<div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = limit + warpId; i &lt; numVecs; i += numWarps) {</div>
<div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;      vecVal[0] = LoadStore&lt;Half8&gt;::load(&amp;vecs[i * kDims + laneId * 8]);</div>
<div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;</div>
<div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;      <span class="keywordtype">float</span> dist;</div>
<div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;      <span class="keywordflow">if</span> (L2) {</div>
<div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;        dist = l2Distance(queryValA, half4ToFloat4(vecVal[0].a));</div>
<div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;        dist += l2Distance(queryValB, half4ToFloat4(vecVal[0].b));</div>
<div class="line"><a name="l00563"></a><span class="lineno">  563</span>&#160;      } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;        dist = ipDistance(queryValA, half4ToFloat4(vecVal[0].a));</div>
<div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;        dist += ipDistance(queryValB, half4ToFloat4(vecVal[0].b));</div>
<div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;      }</div>
<div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;</div>
<div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;      dist = warpReduceAllSum(dist);</div>
<div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;</div>
<div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;      <span class="keywordflow">if</span> (laneId == 0) {</div>
<div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;        distanceOut[i] = dist;</div>
<div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;      }</div>
<div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;    }</div>
<div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;  }</div>
<div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;};</div>
<div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;</div>
<div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> Dims, <span class="keywordtype">bool</span> L2, <span class="keyword">typename</span> T&gt;</div>
<div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;__global__ <span class="keywordtype">void</span></div>
<div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;ivfFlatScan(Tensor&lt;float, 2, true&gt; queries,</div>
<div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;            Tensor&lt;int, 2, true&gt; listIds,</div>
<div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;            <span class="keywordtype">void</span>** allListData,</div>
<div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;            <span class="keywordtype">int</span>* listLengths,</div>
<div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;            Tensor&lt;int, 2, true&gt; prefixSumOffsets,</div>
<div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;            Tensor&lt;float, 1, true&gt; distance) {</div>
<div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160;  <span class="keyword">auto</span> queryId = blockIdx.y;</div>
<div class="line"><a name="l00588"></a><span class="lineno">  588</span>&#160;  <span class="keyword">auto</span> probeId = blockIdx.x;</div>
<div class="line"><a name="l00589"></a><span class="lineno">  589</span>&#160;</div>
<div class="line"><a name="l00590"></a><span class="lineno">  590</span>&#160;  <span class="comment">// This is where we start writing out data</span></div>
<div class="line"><a name="l00591"></a><span class="lineno">  591</span>&#160;  <span class="comment">// We ensure that before the array (at offset -1), there is a 0 value</span></div>
<div class="line"><a name="l00592"></a><span class="lineno">  592</span>&#160;  <span class="keywordtype">int</span> outBase = *(prefixSumOffsets[queryId][probeId].data() - 1);</div>
<div class="line"><a name="l00593"></a><span class="lineno">  593</span>&#160;</div>
<div class="line"><a name="l00594"></a><span class="lineno">  594</span>&#160;  <span class="keyword">auto</span> listId = listIds[queryId][probeId];</div>
<div class="line"><a name="l00595"></a><span class="lineno">  595</span>&#160;  <span class="comment">// Safety guard in case NaNs in input cause no list ID to be generated</span></div>
<div class="line"><a name="l00596"></a><span class="lineno">  596</span>&#160;  <span class="keywordflow">if</span> (listId == -1) {</div>
<div class="line"><a name="l00597"></a><span class="lineno">  597</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00598"></a><span class="lineno">  598</span>&#160;  }</div>
<div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;</div>
<div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;  <span class="keyword">auto</span> query = queries[queryId].data();</div>
<div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;  <span class="keyword">auto</span> vecs = allListData[listId];</div>
<div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;  <span class="keyword">auto</span> numVecs = listLengths[listId];</div>
<div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;  <span class="keyword">auto</span> dim = queries.getSize(1);</div>
<div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;  <span class="keyword">auto</span> distanceOut = distance[outBase].data();</div>
<div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;</div>
<div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;  IVFFlatScan&lt;Dims, L2, T&gt;::scan(query, vecs, numVecs, dim, distanceOut);</div>
<div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;}</div>
<div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;</div>
<div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;<span class="keywordtype">void</span></div>
<div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;runIVFFlatScanTile(Tensor&lt;float, 2, true&gt;&amp; queries,</div>
<div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;                   Tensor&lt;int, 2, true&gt;&amp; listIds,</div>
<div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;                   thrust::device_vector&lt;void*&gt;&amp; listData,</div>
<div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;                   thrust::device_vector&lt;void*&gt;&amp; listIndices,</div>
<div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;                   IndicesOptions indicesOptions,</div>
<div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;                   thrust::device_vector&lt;int&gt;&amp; listLengths,</div>
<div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;                   Tensor&lt;char, 1, true&gt;&amp; thrustMem,</div>
<div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;                   Tensor&lt;int, 2, true&gt;&amp; prefixSumOffsets,</div>
<div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;                   Tensor&lt;float, 1, true&gt;&amp; allDistances,</div>
<div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;                   Tensor&lt;float, 3, true&gt;&amp; heapDistances,</div>
<div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;                   Tensor&lt;int, 3, true&gt;&amp; heapIndices,</div>
<div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;                   <span class="keywordtype">int</span> k,</div>
<div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;                   <span class="keywordtype">bool</span> l2Distance,</div>
<div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;                   <span class="keywordtype">bool</span> useFloat16,</div>
<div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;                   Tensor&lt;float, 2, true&gt;&amp; outDistances,</div>
<div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160;                   Tensor&lt;long, 2, true&gt;&amp; outIndices,</div>
<div class="line"><a name="l00626"></a><span class="lineno">  626</span>&#160;                   cudaStream_t stream) {</div>
<div class="line"><a name="l00627"></a><span class="lineno">  627</span>&#160;  <span class="comment">// Calculate offset lengths, so we know where to write out</span></div>
<div class="line"><a name="l00628"></a><span class="lineno">  628</span>&#160;  <span class="comment">// intermediate results</span></div>
<div class="line"><a name="l00629"></a><span class="lineno">  629</span>&#160;  runCalcListOffsets(listIds, listLengths, prefixSumOffsets, thrustMem, stream);</div>
<div class="line"><a name="l00630"></a><span class="lineno">  630</span>&#160;</div>
<div class="line"><a name="l00631"></a><span class="lineno">  631</span>&#160;  <span class="comment">// Calculate distances for vectors within our chunk of lists</span></div>
<div class="line"><a name="l00632"></a><span class="lineno">  632</span>&#160;  constexpr <span class="keywordtype">int</span> kMaxThreadsIVF = 512;</div>
<div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;</div>
<div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;  <span class="comment">// FIXME: if `half` and # dims is multiple of 2, halve the</span></div>
<div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;  <span class="comment">// threadblock size</span></div>
<div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;</div>
<div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;  <span class="keywordtype">int</span> dim = queries.getSize(1);</div>
<div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;  <span class="keywordtype">int</span> numThreads = std::min(dim, kMaxThreadsIVF);</div>
<div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;</div>
<div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;  <span class="keyword">auto</span> grid = dim3(listIds.getSize(1),</div>
<div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;                   listIds.getSize(0));</div>
<div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;  <span class="keyword">auto</span> block = dim3(numThreads);</div>
<div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;  <span class="comment">// All exact dim kernels are unrolled by 4, hence the `4`</span></div>
<div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;  <span class="keyword">auto</span> smem = <span class="keyword">sizeof</span>(float) * utils::divUp(numThreads, kWarpSize) * 4;</div>
<div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;</div>
<div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;<span class="preprocessor">#define RUN_IVF_FLAT(DIMS, L2, T)                                       \</span></div>
<div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;<span class="preprocessor">  do {                                                                  \</span></div>
<div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;<span class="preprocessor">    ivfFlatScan&lt;DIMS, L2, T&gt;                                            \</span></div>
<div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;<span class="preprocessor">      &lt;&lt;&lt;grid, block, smem, stream&gt;&gt;&gt;(                                  \</span></div>
<div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;<span class="preprocessor">        queries,                                                        \</span></div>
<div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;<span class="preprocessor">        listIds,                                                        \</span></div>
<div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;<span class="preprocessor">        listData.data().get(),                                          \</span></div>
<div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;<span class="preprocessor">        listLengths.data().get(),                                       \</span></div>
<div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;<span class="preprocessor">        prefixSumOffsets,                                               \</span></div>
<div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;<span class="preprocessor">        allDistances);                                                  \</span></div>
<div class="line"><a name="l00656"></a><span class="lineno">  656</span>&#160;<span class="preprocessor">  } while (0)</span></div>
<div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;<span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;<span class="preprocessor">#define HANDLE_DIM_CASE(DIMS)                   \</span></div>
<div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;<span class="preprocessor">  do {                                          \</span></div>
<div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;<span class="preprocessor">    if (l2Distance) {                           \</span></div>
<div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;<span class="preprocessor">      if (useFloat16) {                         \</span></div>
<div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, true, half);         \</span></div>
<div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;<span class="preprocessor">      } else {                                  \</span></div>
<div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, true, float);        \</span></div>
<div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;<span class="preprocessor">      }                                         \</span></div>
<div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;<span class="preprocessor">    } else {                                    \</span></div>
<div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;<span class="preprocessor">      if (useFloat16) {                         \</span></div>
<div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, false, half);        \</span></div>
<div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;<span class="preprocessor">      } else {                                  \</span></div>
<div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, false, float);       \</span></div>
<div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;<span class="preprocessor">      }                                         \</span></div>
<div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;<span class="preprocessor">    }                                           \</span></div>
<div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;<span class="preprocessor">  } while (0)</span></div>
<div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#else</span></div>
<div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;<span class="preprocessor">#define HANDLE_DIM_CASE(DIMS)                   \</span></div>
<div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;<span class="preprocessor">  do {                                          \</span></div>
<div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;<span class="preprocessor">    if (l2Distance) {                           \</span></div>
<div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;<span class="preprocessor">      if (useFloat16) {                         \</span></div>
<div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;<span class="preprocessor">        FAISS_ASSERT(false);                    \</span></div>
<div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;<span class="preprocessor">      } else {                                  \</span></div>
<div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, true, float);        \</span></div>
<div class="line"><a name="l00685"></a><span class="lineno">  685</span>&#160;<span class="preprocessor">      }                                         \</span></div>
<div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;<span class="preprocessor">    } else {                                    \</span></div>
<div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;<span class="preprocessor">      if (useFloat16) {                         \</span></div>
<div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;<span class="preprocessor">        FAISS_ASSERT(false);                    \</span></div>
<div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;<span class="preprocessor">      } else {                                  \</span></div>
<div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;<span class="preprocessor">        RUN_IVF_FLAT(DIMS, false, float);       \</span></div>
<div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;<span class="preprocessor">      }                                         \</span></div>
<div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;<span class="preprocessor">    }                                           \</span></div>
<div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;<span class="preprocessor">  } while (0)</span></div>
<div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;<span class="preprocessor">#endif // FAISS_USE_FLOAT16</span></div>
<div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00697"></a><span class="lineno">  697</span>&#160;  <span class="keywordflow">if</span> (dim == 64) {</div>
<div class="line"><a name="l00698"></a><span class="lineno">  698</span>&#160;    HANDLE_DIM_CASE(64);</div>
<div class="line"><a name="l00699"></a><span class="lineno">  699</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (dim == 128) {</div>
<div class="line"><a name="l00700"></a><span class="lineno">  700</span>&#160;    HANDLE_DIM_CASE(128);</div>
<div class="line"><a name="l00701"></a><span class="lineno">  701</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (dim == 256) {</div>
<div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;    HANDLE_DIM_CASE(256);</div>
<div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (dim &lt;= kMaxThreadsIVF) {</div>
<div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;    HANDLE_DIM_CASE(0);</div>
<div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;  } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;    HANDLE_DIM_CASE(-1);</div>
<div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;  }</div>
<div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;</div>
<div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;  CUDA_TEST_ERROR();</div>
<div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;</div>
<div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;<span class="preprocessor">#undef HANDLE_DIM_CASE</span></div>
<div class="line"><a name="l00712"></a><span class="lineno">  712</span>&#160;<span class="preprocessor"></span><span class="preprocessor">#undef RUN_IVF_FLAT</span></div>
<div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;<span class="preprocessor"></span></div>
<div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;  <span class="comment">// k-select the output in chunks, to increase parallelism</span></div>
<div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;  runPass1SelectLists(prefixSumOffsets,</div>
<div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;                      allDistances,</div>
<div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;                      listIds.getSize(1),</div>
<div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;                      k,</div>
<div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;                      !l2Distance, <span class="comment">// L2 distance chooses smallest</span></div>
<div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;                      heapDistances,</div>
<div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;                      heapIndices,</div>
<div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160;                      stream);</div>
<div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;</div>
<div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;  <span class="comment">// k-select final output</span></div>
<div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;  <span class="keyword">auto</span> flatHeapDistances = heapDistances.downcastInner&lt;2&gt;();</div>
<div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;  <span class="keyword">auto</span> flatHeapIndices = heapIndices.downcastInner&lt;2&gt;();</div>
<div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;</div>
<div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;  runPass2SelectLists(flatHeapDistances,</div>
<div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;                      flatHeapIndices,</div>
<div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;                      listIndices,</div>
<div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;                      indicesOptions,</div>
<div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;                      prefixSumOffsets,</div>
<div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;                      listIds,</div>
<div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;                      k,</div>
<div class="line"><a name="l00735"></a><span class="lineno">  735</span>&#160;                      !l2Distance, <span class="comment">// L2 distance chooses smallest</span></div>
<div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;                      outDistances,</div>
<div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160;                      outIndices,</div>
<div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160;                      stream);</div>
<div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;}</div>
<div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;</div>
<div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;<span class="keywordtype">void</span></div>
<div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;runIVFFlatScan(Tensor&lt;float, 2, true&gt;&amp; queries,</div>
<div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;               Tensor&lt;int, 2, true&gt;&amp; listIds,</div>
<div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;               thrust::device_vector&lt;void*&gt;&amp; listData,</div>
<div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;               thrust::device_vector&lt;void*&gt;&amp; listIndices,</div>
<div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;               IndicesOptions indicesOptions,</div>
<div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;               thrust::device_vector&lt;int&gt;&amp; listLengths,</div>
<div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;               <span class="keywordtype">int</span> maxListLength,</div>
<div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;               <span class="keywordtype">int</span> k,</div>
<div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;               <span class="keywordtype">bool</span> l2Distance,</div>
<div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;               <span class="keywordtype">bool</span> useFloat16,</div>
<div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;               <span class="comment">// output</span></div>
<div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;               Tensor&lt;float, 2, true&gt;&amp; outDistances,</div>
<div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;               <span class="comment">// output</span></div>
<div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;               Tensor&lt;long, 2, true&gt;&amp; outIndices,</div>
<div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;               GpuResources* res) {</div>
<div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;  constexpr <span class="keywordtype">int</span> kMinQueryTileSize = 8;</div>
<div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;  constexpr <span class="keywordtype">int</span> kMaxQueryTileSize = 128;</div>
<div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;  constexpr <span class="keywordtype">int</span> kThrustMemSize = 16384;</div>
<div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;</div>
<div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;  <span class="keywordtype">int</span> nprobe = listIds.getSize(1);</div>
<div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;</div>
<div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;  <span class="keyword">auto</span>&amp; mem = res-&gt;getMemoryManagerCurrentDevice();</div>
<div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;  <span class="keyword">auto</span> stream = res-&gt;getDefaultStreamCurrentDevice();</div>
<div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;</div>
<div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;  <span class="comment">// Make a reservation for Thrust to do its dirty work (global memory</span></div>
<div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;  <span class="comment">// cross-block reduction space); hopefully this is large enough.</span></div>
<div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;  DeviceTensor&lt;char, 1, true&gt; thrustMem1(</div>
<div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;    mem, {kThrustMemSize}, stream);</div>
<div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;  DeviceTensor&lt;char, 1, true&gt; thrustMem2(</div>
<div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;    mem, {kThrustMemSize}, stream);</div>
<div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;  DeviceTensor&lt;char, 1, true&gt;* thrustMem[2] =</div>
<div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;    {&amp;thrustMem1, &amp;thrustMem2};</div>
<div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;</div>
<div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;  <span class="comment">// How much temporary storage is available?</span></div>
<div class="line"><a name="l00776"></a><span class="lineno">  776</span>&#160;  <span class="comment">// If possible, we&#39;d like to fit within the space available.</span></div>
<div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;  <span class="keywordtype">size_t</span> sizeAvailable = mem.getSizeAvailable();</div>
<div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;</div>
<div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;  <span class="comment">// We run two passes of heap selection</span></div>
<div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;  <span class="comment">// This is the size of the first-level heap passes</span></div>
<div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;  constexpr <span class="keywordtype">int</span> kNProbeSplit = 8;</div>
<div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;  <span class="keywordtype">int</span> pass2Chunks = std::min(nprobe, kNProbeSplit);</div>
<div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;</div>
<div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;  <span class="keywordtype">size_t</span> sizeForFirstSelectPass =</div>
<div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;    pass2Chunks * k * (<span class="keyword">sizeof</span>(float) + <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>));</div>
<div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;</div>
<div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;  <span class="comment">// How much temporary storage we need per each query</span></div>
<div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;  <span class="keywordtype">size_t</span> sizePerQuery =</div>
<div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;    2 * <span class="comment">// # streams</span></div>
<div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;    ((nprobe * <span class="keyword">sizeof</span>(int) + <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>)) + <span class="comment">// prefixSumOffsets</span></div>
<div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160;     nprobe * maxListLength * <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>) + <span class="comment">// allDistances</span></div>
<div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;     sizeForFirstSelectPass);</div>
<div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;</div>
<div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;  <span class="keywordtype">int</span> queryTileSize = (int) (sizeAvailable / sizePerQuery);</div>
<div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;</div>
<div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;  <span class="keywordflow">if</span> (queryTileSize &lt; kMinQueryTileSize) {</div>
<div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;    queryTileSize = kMinQueryTileSize;</div>
<div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (queryTileSize &gt; kMaxQueryTileSize) {</div>
<div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;    queryTileSize = kMaxQueryTileSize;</div>
<div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;  }</div>
<div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;</div>
<div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;  <span class="comment">// FIXME: we should adjust queryTileSize to deal with this, since</span></div>
<div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;  <span class="comment">// indexing is in int32</span></div>
<div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;  FAISS_ASSERT(queryTileSize * nprobe * maxListLength &lt;</div>
<div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;         std::numeric_limits&lt;int&gt;::max());</div>
<div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;</div>
<div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;  <span class="comment">// Temporary memory buffers</span></div>
<div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;  <span class="comment">// Make sure there is space prior to the start which will be 0, and</span></div>
<div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;  <span class="comment">// will handle the boundary condition without branches</span></div>
<div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;  DeviceTensor&lt;int, 1, true&gt; prefixSumOffsetSpace1(</div>
<div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;    mem, {queryTileSize * nprobe + 1}, stream);</div>
<div class="line"><a name="l00812"></a><span class="lineno">  812</span>&#160;  DeviceTensor&lt;int, 1, true&gt; prefixSumOffsetSpace2(</div>
<div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;    mem, {queryTileSize * nprobe + 1}, stream);</div>
<div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160;</div>
<div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;  DeviceTensor&lt;int, 2, true&gt; prefixSumOffsets1(</div>
<div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;    prefixSumOffsetSpace1[1].data(),</div>
<div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160;    {queryTileSize, nprobe});</div>
<div class="line"><a name="l00818"></a><span class="lineno">  818</span>&#160;  DeviceTensor&lt;int, 2, true&gt; prefixSumOffsets2(</div>
<div class="line"><a name="l00819"></a><span class="lineno">  819</span>&#160;    prefixSumOffsetSpace2[1].data(),</div>
<div class="line"><a name="l00820"></a><span class="lineno">  820</span>&#160;    {queryTileSize, nprobe});</div>
<div class="line"><a name="l00821"></a><span class="lineno">  821</span>&#160;  DeviceTensor&lt;int, 2, true&gt;* prefixSumOffsets[2] =</div>
<div class="line"><a name="l00822"></a><span class="lineno">  822</span>&#160;    {&amp;prefixSumOffsets1, &amp;prefixSumOffsets2};</div>
<div class="line"><a name="l00823"></a><span class="lineno">  823</span>&#160;</div>
<div class="line"><a name="l00824"></a><span class="lineno">  824</span>&#160;  <span class="comment">// Make sure the element before prefixSumOffsets is 0, since we</span></div>
<div class="line"><a name="l00825"></a><span class="lineno">  825</span>&#160;  <span class="comment">// depend upon simple, boundary-less indexing to get proper results</span></div>
<div class="line"><a name="l00826"></a><span class="lineno">  826</span>&#160;  CUDA_VERIFY(cudaMemsetAsync(prefixSumOffsetSpace1.data(),</div>
<div class="line"><a name="l00827"></a><span class="lineno">  827</span>&#160;                              0,</div>
<div class="line"><a name="l00828"></a><span class="lineno">  828</span>&#160;                              <span class="keyword">sizeof</span>(int),</div>
<div class="line"><a name="l00829"></a><span class="lineno">  829</span>&#160;                              stream));</div>
<div class="line"><a name="l00830"></a><span class="lineno">  830</span>&#160;  CUDA_VERIFY(cudaMemsetAsync(prefixSumOffsetSpace2.data(),</div>
<div class="line"><a name="l00831"></a><span class="lineno">  831</span>&#160;                              0,</div>
<div class="line"><a name="l00832"></a><span class="lineno">  832</span>&#160;                              <span class="keyword">sizeof</span>(int),</div>
<div class="line"><a name="l00833"></a><span class="lineno">  833</span>&#160;                              stream));</div>
<div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;</div>
<div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;  DeviceTensor&lt;float, 1, true&gt; allDistances1(</div>
<div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160;    mem, {queryTileSize * nprobe * maxListLength}, stream);</div>
<div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;  DeviceTensor&lt;float, 1, true&gt; allDistances2(</div>
<div class="line"><a name="l00838"></a><span class="lineno">  838</span>&#160;    mem, {queryTileSize * nprobe * maxListLength}, stream);</div>
<div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;  DeviceTensor&lt;float, 1, true&gt;* allDistances[2] =</div>
<div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160;    {&amp;allDistances1, &amp;allDistances2};</div>
<div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160;</div>
<div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160;  DeviceTensor&lt;float, 3, true&gt; heapDistances1(</div>
<div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;  DeviceTensor&lt;float, 3, true&gt; heapDistances2(</div>
<div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;  DeviceTensor&lt;float, 3, true&gt;* heapDistances[2] =</div>
<div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;    {&amp;heapDistances1, &amp;heapDistances2};</div>
<div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;</div>
<div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;  DeviceTensor&lt;int, 3, true&gt; heapIndices1(</div>
<div class="line"><a name="l00850"></a><span class="lineno">  850</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160;  DeviceTensor&lt;int, 3, true&gt; heapIndices2(</div>
<div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;    mem, {queryTileSize, pass2Chunks, k}, stream);</div>
<div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;  DeviceTensor&lt;int, 3, true&gt;* heapIndices[2] =</div>
<div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;    {&amp;heapIndices1, &amp;heapIndices2};</div>
<div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;</div>
<div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;  <span class="keyword">auto</span> streams = res-&gt;getAlternateStreamsCurrentDevice();</div>
<div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;  streamWait(streams, {stream});</div>
<div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;</div>
<div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;  <span class="keywordtype">int</span> curStream = 0;</div>
<div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;</div>
<div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> query = 0; query &lt; queries.getSize(0); query += queryTileSize) {</div>
<div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;    <span class="keywordtype">int</span> numQueriesInTile =</div>
<div class="line"><a name="l00863"></a><span class="lineno">  863</span>&#160;      std::min(queryTileSize, queries.getSize(0) - query);</div>
<div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;</div>
<div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160;    <span class="keyword">auto</span> prefixSumOffsetsView =</div>
<div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;      prefixSumOffsets[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;</div>
<div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;    <span class="keyword">auto</span> listIdsView =</div>
<div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;      listIds.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160;    <span class="keyword">auto</span> queryView =</div>
<div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;      queries.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160;</div>
<div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;    <span class="keyword">auto</span> heapDistancesView =</div>
<div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;      heapDistances[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;    <span class="keyword">auto</span> heapIndicesView =</div>
<div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;      heapIndices[curStream]-&gt;narrowOutermost(0, numQueriesInTile);</div>
<div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160;</div>
<div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;    <span class="keyword">auto</span> outDistanceView =</div>
<div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;      outDistances.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;    <span class="keyword">auto</span> outIndicesView =</div>
<div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;      outIndices.narrowOutermost(query, numQueriesInTile);</div>
<div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;</div>
<div class="line"><a name="l00883"></a><span class="lineno">  883</span>&#160;    runIVFFlatScanTile(queryView,</div>
<div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;                       listIdsView,</div>
<div class="line"><a name="l00885"></a><span class="lineno">  885</span>&#160;                       listData,</div>
<div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;                       listIndices,</div>
<div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;                       indicesOptions,</div>
<div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;                       listLengths,</div>
<div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;                       *thrustMem[curStream],</div>
<div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;                       prefixSumOffsetsView,</div>
<div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;                       *allDistances[curStream],</div>
<div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;                       heapDistancesView,</div>
<div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;                       heapIndicesView,</div>
<div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;                       k,</div>
<div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;                       l2Distance,</div>
<div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160;                       useFloat16,</div>
<div class="line"><a name="l00897"></a><span class="lineno">  897</span>&#160;                       outDistanceView,</div>
<div class="line"><a name="l00898"></a><span class="lineno">  898</span>&#160;                       outIndicesView,</div>
<div class="line"><a name="l00899"></a><span class="lineno">  899</span>&#160;                       streams[curStream]);</div>
<div class="line"><a name="l00900"></a><span class="lineno">  900</span>&#160;</div>
<div class="line"><a name="l00901"></a><span class="lineno">  901</span>&#160;    curStream = (curStream + 1) % 2;</div>
<div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;  }</div>
<div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160;</div>
<div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160;  streamWait({stream}, streams);</div>
<div class="line"><a name="l00905"></a><span class="lineno">  905</span>&#160;}</div>
<div class="line"><a name="l00906"></a><span class="lineno">  906</span>&#160;</div>
<div class="line"><a name="l00907"></a><span class="lineno">  907</span>&#160;} } <span class="comment">// namespace</span></div>
<div class="ttc" id="structfaiss_1_1gpu_1_1LoadStore_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1LoadStore.html">faiss::gpu::LoadStore</a></div><div class="ttdef"><b>Definition:</b> <a href="LoadStoreOperators_8cuh_source.html#l00030">LoadStoreOperators.cuh:30</a></div></div>
<div class="ttc" id="structfaiss_1_1gpu_1_1Math_html_a4b17f0b5d014f300e76dde5b24af8014"><div class="ttname"><a href="structfaiss_1_1gpu_1_1Math.html#a4b17f0b5d014f300e76dde5b24af8014">faiss::gpu::Math::reduceAdd</a></div><div class="ttdeci">static __device__ T reduceAdd(T v)</div><div class="ttdoc">For a vector type, this is a horizontal add, returning sum(v_i) </div><div class="ttdef"><b>Definition:</b> <a href="MathOperators_8cuh_source.html#l00044">MathOperators.cuh:44</a></div></div>
<div class="ttc" id="structfaiss_1_1gpu_1_1ConvertTo_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1ConvertTo.html">faiss::gpu::ConvertTo</a></div><div class="ttdef"><b>Definition:</b> <a href="ConversionOperators_8cuh_source.html#l00023">ConversionOperators.cuh:23</a></div></div>
<div class="ttc" id="structfaiss_1_1gpu_1_1IVFFlatScan_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1IVFFlatScan.html">faiss::gpu::IVFFlatScan</a></div><div class="ttdoc">The class that we use to provide scan specializations. </div><div class="ttdef"><b>Definition:</b> <a href="IVFFlatScan_8cu_source.html#l00046">IVFFlatScan.cu:46</a></div></div>
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